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Record W2113807053 · doi:10.2118/02-06-05

A Comparative Study of Hydraulic Models for Foam Drilling

2002· article· en· W2113807053 on OpenAlexaff
M. E. Ozbayoglu, Ergün Kuru, Stefan Miska, Nicholas Takach

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2002
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of Alberta
FundersUniversity of Tulsa
KeywordsDrilling fluidCompressibilityRheologyFlow (mathematics)DrillingMechanicsPressure dropVolumetric flow rateMaterials scienceMechanical engineeringPetroleum engineeringGeotechnical engineeringEngineeringComposite materialPhysics

Abstract

fetched live from OpenAlex

Abstract Compared to conventional (incompressible) drilling fluids, relatively little is known about the hydraulic and rheological properties of foamed drilling fluids. The complex flow mechanisms involved in compressible drilling fluid circulation make determination of the optimum combination of liquid and gas injection rates very difficult. Modelling of foam rheology is the key issue in hydraulic design, in order to predict the bottom-hole pressure accurately, and to optimize the different controllable variables for effective cutting transport performance. The University of Tulsa's low-pressure ambient temperature flow loop has been recently modified to accommodate foam flow. The flow loop permits foam flow through 0.0508 m (2 in.), 0.0762 m (3 in.), 0.1016 m (4 in.) diameter pipes, and a 0.2032 m (8 in.) by 0.1143 m (41/2 in.) annular section. Preliminary experiments have been conducted, in which pressure losses were measured for different foam qualities. Measured parameters were gas/liquid flow rates, pressure, differential pressure loss, and temperature. Statistical analysis was carried out to see the degree of fit provided by Bingham plastic, power law, and yield power law models for the generalized foam flow curve data. A comparative study was conducted to investigate the predictive ability of the available foam hydraulic models. Models presented by Beyer et al. (1972), Blauer et al. (1974), Reidenbach et al. (1986), Sanghani and Ikoku (1983), Gardiner et al. (1988) and Valko and Economides (1992) were used to estimate the frictional pressure losses during the flow of foam in horizontal pipes. Comparison of the model predictions with experimental pressure loss values show that model predictions of frictional pressure losses can be different from the actual values by 2 to 250 %. Introduction In the 1970s, high quality foams were developed into a viable fracturing stimulation tool for oil and gas wells(1). Since then, foam rheology has been the subject of numerous investigations, in an effort to design better proppant transport medium. Lord(2) presented one of the first comprehensive mathematical treatments of foam flow behaviour. He used the real gas law and mass balance considerations to develop an equation of state for foam with solids. Later, Spoerker et al.(3) modified Lord's solution and presented a new two-phase flow equation. They used a virial equation(4) instead of the real gas equation of state. They also solved the differential mechanical energy equation to obtain an explicit expresion for pressure loss prediction during foam flow. Reidenbach et al.(5) presented empirical correlations to calculate the rheological properties of N2 and CO2 foam fracturing fluids. Harris(6–9) conducted some excellent studies on the rheology and fluid loss properties of fracturing fluids. Harris and Reidenbach(10) also studied the effect of temperature on the rheology of foam fracturing fluids. Foam has been used as a drilling fluid in many drilling operations, and the results from various field cases are well documented in the literature(11–23).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.210
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2002
Admission routes1
Has abstractyes

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